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docs: update roadmap & text2sql

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@ -84,32 +84,81 @@ Currently, we have released multiple key features, which are listed below to dem
- ChatDashboard
- Multi-Agents&Plugins
- Unified vector storage/indexing of knowledge base
- Support for unstructured data such as PDF, TXT, Markdown, CSV, DOC, PPT, and WebURL
- Support for unstructured data
- PDF
- TXT
- Markdown
- CSV
- DOC
- PPT
- WebURL
- Multi LLMs Support, Supports multiple large language models, currently supporting
- 🔥 InternLM(7b,20b)
- 🔥 Baichuan2(7b,13b)
- 🔥 Vicuna-v1.5(7b,13b)
- 🔥 llama-2(7b,13b,70b)
- WizardLM-v1.2(13b)
- Vicuna (7b,13b)
- ChatGLM-6b (int4,int8)
- ChatGLM2-6b (int4,int8)
- guanaco(7b,13b,33b)
- Gorilla(7b,13b)
- baichuan(7b,13b)
- [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
- [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)
- [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
- [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
- [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
- [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
- [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
- [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
- [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg)
- [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5)
- [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b)
- [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
- [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b)
- [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
- [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
- [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
- [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
- [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
- [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
- [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
- [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)
- [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
- [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)
- [all models of OpenOrca](https://huggingface.co/Open-Orca)
- [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)
- [VMware's OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
- Support API Proxy LLMs
- [x] ChatGPT
- [x] Tongyi
- [x] Wenxin
- [x] Spark
- [x] MiniMax
- [x] ChatGLM
## Introduction
DB-GPT creates a vast model operating system using [FastChat](https://github.com/lm-sys/FastChat) and offers a large language model powered by vicuna. In addition, we provide private domain knowledge base question-answering capability. Furthermore, we also provide support for additional plugins, and our design natively supports the Auto-GPT plugin.Our vision is to make it easier and more convenient to build applications around databases and llm.
- Support Datasources
| DataSource | support | Notes |
| ------------------------------------------------------------------------------ | ----------- | ------------------------------------------- |
| [MySQL](https://www.mysql.com/) | Yes | |
| [PostgresSQL](https://www.postgresql.org/) | Yes | |
| [Spark](https://github.com/apache/spark) | Yes | |
| [DuckDB](https://github.com/duckdb/duckdb) | Yes | |
| [Sqlite](https://github.com/sqlite/sqlite) | Yes | |
| [MSSQL](https://github.com/microsoft/mssql-jdbc) | Yes | |
| [ClickHouse](https://github.com/ClickHouse/ClickHouse) | Yes | |
| [Oracle](https://github.com/oracle) | No | TODO |
| [Redis](https://github.com/redis/redis) | No | TODO |
| [MongoDB](https://github.com/mongodb/mongo) | No | TODO |
| [HBase](https://github.com/apache/hbase) | No | TODO |
| [Doris](https://github.com/apache/doris) | No | TODO |
| [DB2](https://github.com/IBM/Db2) | No | TODO |
| [Couchbase](https://github.com/couchbase) | No | TODO |
| [Elasticsearch](https://github.com/elastic/elasticsearch) | No | TODO |
| [OceanBase](https://github.com/OceanBase) | No | TODO |
| [TiDB](https://github.com/pingcap/tidb) | No | TODO |
| [StarRocks](https://github.com/StarRocks/starrocks) | No | TODO |
## Introduction
Is the architecture of the entire DB-GPT shown in the following figure:
<p align="center">
@ -117,16 +166,16 @@ Is the architecture of the entire DB-GPT shown in the following figure:
</p>
The core capabilities mainly consist of the following parts:
1. Knowledge base capability: Supports private domain knowledge base question-answering capability.
2. Large-scale model management capability: Provides a large model operating environment based on FastChat.
3. Unified data vector storage and indexing: Provides a uniform way to store and index various data types.
4. Connection module: Used to connect different modules and data sources to achieve data flow and interaction.
5. Agent and plugins: Provides Agent and plugin mechanisms, allowing users to customize and enhance the system's behavior.
6. Prompt generation and optimization: Automatically generates high-quality prompts and optimizes them to improve system response efficiency.
7. Multi-platform product interface: Supports various client products, such as web, mobile applications, and desktop applications.
1. Multi-Models: Support multi-LLMs, such as LLaMA/LLaMA2、CodeLLaMA、ChatGLM, QWen、Vicuna and proxy model ChatGPT、Baichuan、tongyi、wenxin etc
2. Knowledge Based QA: You can perform high-quality intelligent Q&A based on local documents such as pdf, word, excel and other data.
3. Embedding: Unified data vector storage and indexing, Embed data as vectors and store them in vector databases, providing content similarity search.
4. Multi-Datasources: Used to connect different modules and data sources to achieve data flow and interaction.
5. Multi-Agents: Provides Agent and plugin mechanisms, allowing users to customize and enhance the system's behavior.
6. Privacy & Secure: You can be assured that there is no risk of data leakage, and your data is 100% private and secure.
7. Text2SQL: We enhance the Text-to-SQL performance by applying Supervised Fine-Tuning (SFT) on large language models
### SubModule
- [DB-GPT-Hub](https://github.com/eosphoros-ai/DB-GPT-Hub) Text-to-SQL parsing with LLMs
- [DB-GPT-Hub](https://github.com/eosphoros-ai/DB-GPT-Hub) Text-to-SQL performance by applying Supervised Fine-Tuning (SFT) on large language models.
- [DB-GPT-Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins) DB-GPT Plugins, Can run autogpt plugin directly
- [DB-GPT-Web](https://github.com/eosphoros-ai/DB-GPT-Web) ChatUI for DB-GPT
@ -155,122 +204,81 @@ The core capabilities mainly consist of the following parts:
</p>
### KBQA RAG optimization
- [] KnownledgeGraph
- [x] Multi Documents
- [x] PDF
- [x] Excel, csv
- [x] Word
- [x] Text
- [x] MarkDown
- [ ] Code
- [ ] Images
- [x]RAG
- [ ]KnownledgeGraph
### Multi Datasource Support
| DataSource | support | Notes |
| ------------------------------------------------------------------------------ | ----------- | ------------------------------------------- |
| [MySQL](https://www.mysql.com/) | Yes | |
| [PostgresSQL](https://www.postgresql.org/) | Yes | |
| [Spark](https://github.com/apache/spark) | Yes | |
| [DuckDB](https://github.com/duckdb/duckdb) | Yes | |
| [Sqlite](https://github.com/sqlite/sqlite) | Yes | |
| [MSSQL](https://github.com/microsoft/mssql-jdbc) | Yes | |
| [ClickHouse](https://github.com/ClickHouse/ClickHouse) | Yes | |
| [Oracle](https://github.com/oracle) | No | TODO |
| [Redis](https://github.com/redis/redis) | No | TODO |
| [MongoDB](https://github.com/mongodb/mongo) | No | TODO |
| [HBase](https://github.com/apache/hbase) | No | TODO |
| [Doris](https://github.com/apache/doris) | No | TODO |
| [DB2](https://github.com/IBM/Db2) | No | TODO |
| [Couchbase](https://github.com/couchbase) | No | TODO |
| [Elasticsearch](https://github.com/elastic/elasticsearch) | No | TODO |
| [OceanBase](https://github.com/OceanBase) | No | TODO |
| [TiDB](https://github.com/pingcap/tidb) | No | TODO |
| [StarRocks](https://github.com/StarRocks/starrocks) | No | TODO |
- Multi Datasource Support
- [x]MySQL
- [x]PostgresSQL
- [x]Spark
- [x]DuckDB
- [x]Sqlite
- [x]MSSQL
- [x]ClickHouse
- [ ]Oracle
- [ ]Redis
- [ ]MongoDB
- [ ]HBase
- [ ]Doris
- [ ]DB2
- [ ]Couchbase
- [ ]Elasticsearch
- [ ]OceanBase
- [ ]TiDB
- [ ]StarRocks
### Multi-Models And vLLM
- [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
- [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)
- [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
- [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
- [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
- [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
- [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
- [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
- [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg)
- [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5)
- [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b)
- [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
- [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b)
- [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
- [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
- [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
- [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
- [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
- [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
- [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
- [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)
- [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
- [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)
- [all models of OpenOrca](https://huggingface.co/Open-Orca)
- [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)
- [VMware&#39;s OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
- [x] [cluster deployment](https://db-gpt.readthedocs.io/en/latest/getting_started/install/cluster/vms/index.html)
- [x] [fastchat support](https://github.com/lm-sys/FastChat)
- [x] [vLLM support](https://db-gpt.readthedocs.io/en/latest/getting_started/install/llm/vllm/vllm.html)
### Agents market and Plugins
- multi-agents framework
- custom plugin development
- plugin market
- [x] multi-agents framework
- [x] custom plugin development
- [ ] plugin market
### Cost and Observability
- [x] [debugging](https://db-gpt.readthedocs.io/en/latest/getting_started/observability.html)
- [ ] Observability
### Text2SQL Finetune
- support llms
- [x]LLaMA
- [x]LLaMA-2
- [x]BLOOM
- [x]BLOOMZ
- [x]Falcon
- [x]Baichuan
- [x]Baichuan2
- [x]InternLM
- [x]Qwen
- [x]XVERSE
- [x]ChatGLM2
| LLMs | Size | Module | Template |
| -------------------------------------------------------- | --------------------------- | ----------------- |----------|
| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | q_proj,v_proj | - |
| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | q_proj,v_proj | llama2 |
| [BLOOM](https://huggingface.co/bigscience/bloom) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [BLOOMZ](https://huggingface.co/bigscience/bloomz) | 560M/1.1B/1.7B/3B/7.1B/176B | query_key_value | - |
| [Falcon](https://huggingface.co/tiiuae/falcon-7b) | 7B/40B | query_key_value | - |
| [Baichuan](https://github.com/baichuan-inc/baichuan-13B) | 7B/13B | W_pack | baichuan |
| [Baichuan2](https://github.com/baichuan-inc/Baichuan2) | 7B/13B | W_pack | baichuan2 |
| [InternLM](https://github.com/InternLM/InternLM) | 7B | q_proj,v_proj | intern |
| [Qwen](https://github.com/QwenLM/Qwen-7B) | 7B | c_attn | chatml |
| [XVERSE](https://github.com/xverse-ai/XVERSE-13B) | 13B | q_proj,v_proj | xverse |
| [ChatGLM2](https://github.com/THUDM/ChatGLM2-6B) | 6B | query_key_value | chatglm2 |
- SFT Accuracy
As of October 10, 2023, by fine-tuning an open-source model of 13 billion parameters using this project, the execution accuracy on the Spider evaluation dataset has surpassed that of GPT-4!
Datasets
| Datasets | License | Link |
| ---------------------- | ------------ | -------------------------------------------------------------------------------------------------------------------- |
| academic | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| advising | CC-BY-4.0 | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| atis | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| restaurants | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| scholar | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| imdb | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| yelp | Not Found | [https://github.com/jkkummerfeld/text2sql-data](https://github.com/jkkummerfeld/text2sql-data) |
| criteria2sql | Apache-2.0 | [https://github.com/xiaojingyu92/Criteria2SQL](https://github.com/xiaojingyu92/Criteria2SQL) |
| css | CC-BY-4.0 | [https://huggingface.co/datasets/zhanghanchong/css](https://huggingface.co/datasets/zhanghanchong/css) |
| eICU | CC-BY-4.0 | [https://github.com/glee4810/EHRSQL](https://github.com/glee4810/EHRSQL) |
| mimic_iii | CC-BY-4.0 | [https://github.com/glee4810/EHRSQL](https://github.com/glee4810/EHRSQL) |
| geonucleardata | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| greatermanchestercrime | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| studentmathscore | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| thehistoryofbaseball | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| uswildfires | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| whatcdhiphop | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| worldsoccerdatabase | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| pesticide | CC-BY-SA-4.0 | [https://github.com/chiahsuan156/KaggleDBQA](https://github.com/chiahsuan156/KaggleDBQA) |
| mimicsql_data | MIT | [https://github.com/wangpinggl/TREQS](https://github.com/wangpinggl/TREQS) |
| nvbench | MIT | [https://github.com/TsinghuaDatabaseGroup/nvBench](https://github.com/TsinghuaDatabaseGroup/nvBench) |
| sede | Apache-2.0 | [https://github.com/hirupert/sede](https://github.com/hirupert/sede) |
| spider | CC-BY-SA-4.0 | [https://huggingface.co/datasets/spider](https://huggingface.co/datasets/spider) |
| sql_create_context | CC-BY-4.0 | [https://huggingface.co/datasets/b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context) |
| squall | CC-BY-SA-4.0 | [https://github.com/tzshi/squall](https://github.com/tzshi/squall) |
| wikisql | BSD 3-Clause | [https://github.com/salesforce/WikiSQL](https://github.com/salesforce/WikiSQL) |
| BIRD | Not Found | https://bird-bench.github.io/ |
| CHASE | MIT LICENSE | https://xjtu-intsoft.github.io/chase/ |
| cosql | Not Found | https://yale-lily.github.io/cosql/ |
| name | Execution Accuracy | reference |
| ----------------------------------| ------------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| **GPT-4** | **0.762** | [numbersstation-eval-res](https://www.numbersstation.ai/post/nsql-llama-2-7b) |
| ChatGPT | 0.728 | [numbersstation-eval-res](https://www.numbersstation.ai/post/nsql-llama-2-7b) |
| **CodeLlama-13b-Instruct-hf_lora**| **0.789** | sft train by our this project,only used spider train dataset ,the same eval way in this project with lora SFT |
| CodeLlama-13b-Instruct-hf_qlora | 0.774 | sft train by our this project,only used spider train dataset ,the same eval way in this project with qlora and nf4,bit4 SFT |
| wizardcoder | 0.610 | [text-to-sql-wizardcoder](https://github.com/cuplv/text-to-sql-wizardcoder/tree/main) |
| CodeLlama-13b-Instruct-hf | 0.556 | eval in this project default param |
| llama2_13b_hf_lora_best | 0.744 | sft train by our this project,only used spider train dataset ,the same eval way in this project |
[More Information about Text2SQL finetune](https://github.com/eosphoros-ai/DB-GPT-Hub)

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README.zh.md
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@ -117,22 +117,75 @@ DB-GPT 是一个开源的以数据库为基础的GPT实验项目，使用本地
- 插件模型
- 知识库统一向量存储/索引
- 非结构化数据支持包括PDF、MarkDown、CSV、WebURL
- 多模型支持
- 多模型支持与管理
- 支持多种大语言模型, 当前已支持如下模型:
- 🔥 InternLM(7b,20b)
- 🔥 Baichuan2(7b,13b)
- 🔥 Vicuna-v1.5(7b,13b)
- 🔥 llama-2(7b,13b,70b)
- WizardLM-v1.2(13b)
- Vicuna (7b,13b)
- ChatGLM-6b (int4,int8)
- ChatGLM2-6b (int4,int8)
- guanaco(7b,13b,33b)
- Gorilla(7b,13b)
- baichuan(7b,13b)
- [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
- [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)
- [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
- [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
- [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
- [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
- [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
- [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
- [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg)
- [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5)
- [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b)
- [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
- [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b)
- [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
- [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
- [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
- [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
- [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
- [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
- [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
- [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)
- [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
- [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)
- [all models of OpenOrca](https://huggingface.co/Open-Orca)
- [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)
- [VMware&#39;s OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
- 支持在线代理模型
- [x] ChatGPT
- [x] Tongyi
- [x] Wenxin
- [x] ChatGLM
- 支持数据源
| DataSource | support | Notes |
| ------------------------------------------------------------------------------ | ----------- | ------------------------------------------- |
| [MySQL](https://www.mysql.com/) | Yes | |
| [PostgresSQL](https://www.postgresql.org/) | Yes | |
| [Spark](https://github.com/apache/spark) | Yes | |
| [DuckDB](https://github.com/duckdb/duckdb) | Yes | |
| [Sqlite](https://github.com/sqlite/sqlite) | Yes | |
| [MSSQL](https://github.com/microsoft/mssql-jdbc) | Yes | |
| [ClickHouse](https://github.com/ClickHouse/ClickHouse) | Yes | |
| [Oracle](https://github.com/oracle) | No | TODO |
| [Redis](https://github.com/redis/redis) | No | TODO |
| [MongoDB](https://github.com/mongodb/mongo) | No | TODO |
| [HBase](https://github.com/apache/hbase) | No | TODO |
| [Doris](https://github.com/apache/doris) | No | TODO |
| [DB2](https://github.com/IBM/Db2) | No | TODO |
| [Couchbase](https://github.com/couchbase) | No | TODO |
| [Elasticsearch](https://github.com/elastic/elasticsearch) | No | TODO |
| [OceanBase](https://github.com/OceanBase) | No | TODO |
| [TiDB](https://github.com/pingcap/tidb) | No | TODO |
| [StarRocks](https://github.com/StarRocks/starrocks) | No | TODO |
## 架构方案
DB-GPT基于 [FastChat](https://github.com/lm-sys/FastChat) 构建大模型运行环境，并提供 vicuna 作为基础的大语言模型。此外，我们通过LangChain提供私域知识库问答能力。同时我们支持插件模式, 在设计上原生支持Auto-GPT插件。我们的愿景是让围绕数据库和LLM构建应用程序更加简便和便捷。
DB-GPT基于 [FastChat](https://github.com/lm-sys/FastChat) 构建大模型运行环境。此外，我们通过LangChain提供私域知识库问答能力。同时我们支持插件模式, 在设计上原生支持Auto-GPT插件。我们的愿景是让围绕数据库和LLM构建应用程序更加简便和便捷。
整个DB-GPT的架构，如下图所示
@ -141,16 +194,16 @@ DB-GPT基于 [FastChat](https://github.com/lm-sys/FastChat) 构建大模型运
</p>
核心能力主要有以下几个部分。
1. 知识库能力：支持私域知识库问答能力
2. 大模型管理能力：基于FastChat提供一个大模型的运营环境。
3. 统一的数据向量化存储与索引：提供一种统一的方式来存储和索引各种数据类型。
4. 连接模块：用于连接不同的模块和数据源，实现数据的流转和交互。
5. Agent与插件：提供Agent和插件机制，使得用户可以自定义并增强系统的行为。
6. Prompt自动生成与优化：自动化生成高质量的Prompt，并进行优化，提高系统的响应效率。
7. 多端产品界面：支持多种不同的客户端产品，例如Web、移动应用和桌面应用等。
1. 多模型：支持多LLM，如LLaMA/LLaMA2、CodeLLaMA、ChatGLM、QWen、Vicuna以及代理模型ChatGPT、Baichuan、tongyi、wenxin等
2. 私域知识库问答: 可以根据本地文档（如pdf、word、excel等数据）进行高质量的智能问答。
3. 统一数据向量存储和索引: 将数据嵌入为向量并存储在向量数据库中，提供内容相似性搜索。
4. 多数据源: 用于连接不同的模块和数据源，实现数据的流动和交互。
5. Agent与插件: 提供Agent和插件机制，使得用户可以自定义并增强系统的行为。
6. 隐私和安全: 您可以放心，没有数据泄露的风险，您的数据100%私密和安全。
7. Text2SQL: 我们通过在大型语言模型监督微调（SFT）来增强文本到SQL的性能
### 子模块
- [DB-GPT-Hub](https://github.com/csunny/DB-GPT-Hub) 使用 LLM 进行文本到 SQL 解析
- [DB-GPT-Hub](https://github.com/csunny/DB-GPT-Hub) 通过微调来持续提升Text2SQL效果
- [DB-GPT-Plugins](https://github.com/csunny/DB-GPT-Plugins) DB-GPT 插件仓库, 兼容Auto-GPT
- [DB-GPT-Web](https://github.com/csunny/DB-GPT-Web) 多端交互前端界面
@ -194,6 +247,84 @@ The MIT License (MIT)
<img src="./assets/roadmap.jpg" width="800px" />
</p>
### 知识库RAG检索优化
- [x] Multi Documents
- [x] PDF
- [x] Excel, csv
- [x] Word
- [x] Text
- [x] MarkDown
- [ ] Code
- [ ] Images
- [x]RAG
- [ ]KnownledgeGraph
### 多数据源支持
- 支持数据源
- [x]MySQL
- [x]PostgresSQL
- [x]Spark
- [x]DuckDB
- [x]Sqlite
- [x]MSSQL
- [x]ClickHouse
- [ ]Oracle
- [ ]Redis
- [ ]MongoDB
- [ ]HBase
- [ ]Doris
- [ ]DB2
- [ ]Couchbase
- [ ]Elasticsearch
- [ ]OceanBase
- [ ]TiDB
- [ ]StarRocks
### 多模型管理与推理优化
- [x] [集群部署](https://db-gpt.readthedocs.io/en/latest/getting_started/install/cluster/vms/index.html)
- [x] [fastchat支持](https://github.com/lm-sys/FastChat)
- [x] [vLLM 支持](https://db-gpt.readthedocs.io/en/latest/getting_started/install/llm/vllm/vllm.html)
### Agents与插件市场
- [x] 多Agents框架
- [x] 自定义Agents
- [ ] 插件市场
### 成本与可观测性
- [x] [debugging](https://db-gpt.readthedocs.io/en/latest/getting_started/observability.html)
- [ ] 可观测性
- [ ] 推理预算
### Text2SQL微调
- support llms
- [x]LLaMA
- [x]LLaMA-2
- [x]BLOOM
- [x]BLOOMZ
- [x]Falcon
- [x]Baichuan
- [x]Baichuan2
- [x]InternLM
- [x]Qwen
- [x]XVERSE
- [x]ChatGLM2
- SFT模型准确率
截止20231010，我们利用本项目基于开源的13B大小的模型微调后，在Spider的评估集上的执行准确率，已经超越GPT-4!
| 模型名称 | 执行准确率 | 说明 |
| ----------------------------------| ------------------ | ------------------------------------------------------------------------------------------------------------------------------ |
| **GPT-4** | **0.762** | [numbersstation-eval-res](https://www.numbersstation.ai/post/nsql-llama-2-7b) |
| ChatGPT | 0.728 | [numbersstation-eval-res](https://www.numbersstation.ai/post/nsql-llama-2-7b) |
| **CodeLlama-13b-Instruct-hf_lora**| **0.789** | sft train by our this project,only used spider train dataset ,the same eval way in this project with lora SFT |
| CodeLlama-13b-Instruct-hf_qlora | 0.774 | sft train by our this project,only used spider train dataset ,the same eval way in this project with qlora and nf4,bit4 SFT |
| wizardcoder | 0.610 | [text-to-sql-wizardcoder](https://github.com/cuplv/text-to-sql-wizardcoder/tree/main) |
| CodeLlama-13b-Instruct-hf | 0.556 | eval in this project default param |
| llama2_13b_hf_lora_best | 0.744 | sft train by our this project,only used spider train dataset ,the same eval way in this project |
[More Information about Text2SQL finetune](https://github.com/eosphoros-ai/DB-GPT-Hub)
## 联系我们
<p align="center">

4
pilot/model/proxy/llms/tongyi.py
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@ -34,7 +34,7 @@ def tongyi_generate_stream(
elif message.role == ModelMessageRoleType.SYSTEM:
history.append({"role": "system", "content": message.content})
elif message.role == ModelMessageRoleType.AI:
history.append({"role": "assistant", "content": message.content})
history.append({"role": "system", "content": message.content})
else:
pass
@ -49,7 +49,7 @@ def tongyi_generate_stream(
history.remove(last_user_input)
history.append(last_user_input)
print("history", history)
print(history)
gen = Generation()
res = gen.call(
proxyllm_backend,